Abstract: In some examples, a predictive model is trained to determine account balances over which funds in user accounts are predicted to be surplus. Data of a first account of a user is input into the trained predictive model to determine a balance over which a portion of funds in the first account are predicted to be surplus funds for a period of time. A user device of the user presents a user interface that indicates predicted expenses and predicted income for a plurality of periods of time including the period of time. The user interface further indicates the surplus funds for the period of time and includes an interactive element for indicating disposition of the surplus funds. Based on receiving, via the user interface, an indication of an action to perform with respect to the surplus funds, at least one instruction is sent for performing the indicated action.

Abstract: In some examples, a system may receive transaction data indicating payments into a first account over time and payments out of the first account over time, the first account associated with a user. In addition, the system may access a data structure including historical account data that indicates variations in a balance of the first account over time. The system may determine an indicated minimum balance for the first account based on inputting the transaction data and the historical account data into a first predictive model configured to predict a minimum balance for enabling predicted payments out of a user account. The system may determine, based on a difference between a current balance of the first account and the predicted minimum balance for the first account, that the first account has a surplus of funds. Based at least on the surplus, the system may send an instruction.

Abstract: Embodiments include systems and techniques including a system configured to obtain a first secured obligation of an obligor to a first obligee. The system is configured to transfer cryptographic assets from an account owned by the obligor to an account owned by the first obligee. The system is configured to obtain a second secured obligation of the obligor to a second obligee. The system is configured to instantiate a smart contract which transfers at least a portion of the cryptographic assets from the account owned by the first obligee to an account owned by the second obligee when the first secured obligation is satisfied. The system is configured to determine that at least some of the obligation of the obligor to the first obligee has been satisfied. The system is configured to cause execution of the smart contract.

Abstract: This disclosure describes, in part, techniques for automating transfers of funds from a deposit account of a user to a savings account of the user based on historical transaction data associated with the deposit account. Using historical deposits and withdrawals from the deposit account, a prediction may be made regarding deposits to, and withdrawals from, the deposit account that will occur in a future period. Based on that that information and a balance to maintain in the deposit account for the duration of the future period, the amount of funds to transfer from the deposit account to the savings account may be determined. The techniques may further include transferring the funds to the savings account once determined.

Abstract: Provided is a process, including for lending, with a smart contract executable by a decentralized computing platform, money to a borrower. The process includes securing, with the smart contract, the loan by obtaining control of cryptocurrency of the borrower and monitoring, via the smart contract, whether the cryptocurrency satisfies a loan-to-value threshold. In response to the monitoring, an amount of cryptocurrency secured with the loan can be adjusted.

Abstract: Provided is a process, including for lending, with a smart contract executable by a decentralized computing platform, money to a borrower. The process includes securing, with the smart contract, the loan by obtaining control of cryptocurrency of the borrower and monitoring, via the smart contract, whether the cryptocurrency satisfies a loan-to-value threshold. In response to the monitoring, an amount of cryptocurrency secured with the loan can be adjusted.

Abstract: In some examples, a system may receive transaction data indicating payments into a first account over time and payments out of the first account over time, the first account associated with a user. In addition, the system may access a data structure including historical account data that indicates variations in a balance of the first account over time. The system may determine an indicated minimum balance for the first account based on inputting the transaction data and the historical account data into a first predictive model configured to a predict a minimum balance for enabling predicted payments out of a user account. The system may determine, based on a difference between a current balance of the first account and the predicted minimum balance for the first account, that the first account has a surplus of funds. Based at least on the surplus, the system may send an instruction.

Abstract: This disclosure describes, in part, techniques for enabling a merchant or other user to obtain needed capital by financing the cost of individual items after the merchant or other user has acquired the item(s) using a financial instrument, such as a credit card, debit card, or the like. For example, an example merchant may purchase, through the course of a month or other time period, multiple items for operation of their business using a credit card provided by a financial institution. Thereafter, a service provider may aggregate these purchases and enable the merchant to request to finance individual item(s). In response to receiving such a request, the service provider can solicit offers from an array of lenders.

Abstract: This disclosure describes, in part, techniques for generating predictive models based on past transaction data and/or future-event data to predict: (i) when an account of user is expected to fall below a minimum balance associated with that user, and/or (ii) when an account has surplus funds that may safely be moved to a higher-yield account for some amount of time. In response to determining a predicted time at which an account is expected to fall below the minimum balance, the techniques may generate an offer to extend capital to the user prior to the predicted time. In response to determining that a user has or will have surplus funds, the techniques may generate an offer to move some or all of these surplus funds into a separate account providing a higher yield than the primary account of the user.

Abstract: This disclosure describes, in part, techniques for generating predictive models based on past transaction data and/or future-event data to predict: (i) when an account of user is expected to fall below a minimum balance associated with that user, and/or (ii) when an account has surplus funds that may safely be moved to a higher-yield account for some amount of time. In response to determining a predicted time at which an account is expected to fall below the minimum balance, the techniques may generate an offer to extend capital to the user prior to the predicted time. In response to determining that a user has or will have surplus funds, the techniques may generate an offer to move some or all of these surplus funds into a separate account providing a higher yield than the primary account of the user.

Abstract: In one embodiment, a method includes receiving, by a payment service system, a payment request to charge a payment card for a transaction. The payment card is associated with a user account maintained by the payment service system and the user account is configured to apply a different interest rate to each of multiple transactions. The method includes in response to receiving the payment request, identifying, by the payment service system, purchase characteristics of the transaction. The method includes determining, by the payment service system, an interest rate to be associated with the payment request based on the identified purchase characteristics and historical repayment data stored in a data store of the payment service system. The method includes upon receiving a payment confirmation from the user, updating, by the payment service system, the user account to include the transaction at the determined interest rate.

Abstract: This disclosure describes, in part, techniques for generating predictive models based on past transaction data and/or future-event data to predict: (i) when an account of user is expected to fall below a minimum balance associated with that user, and/or (ii) when an account has surplus funds that may safely be moved to a higher-yield account for some amount of time. In response to determining a predicted time at which an account is expected to fall below the minimum balance, the techniques may generate an offer to extend capital to the user prior to the predicted time. In response to determining that a user has or will have surplus funds, the techniques may generate an offer to move some or all of these surplus funds into a separate account providing a higher yield than the primary account of the user.